System and method for blocking screenshots and screen recordings of premium user-generated content

1. A method comprising:

receiving, by one or more processors, a first media content frame from a first computer device;

determining, by the one or more processors, that one or more user interface elements are present in the first media content frame;

extracting, by the one or more processors, the one or more user interface elements from the first media content frame;

converting, by the one or more processors, the one or more user interface elements to video;

encrypting, by the one or more processors, the video to prevent screenshot capture of the one or more user interface elements present in the first media content frame by a second computer device lacking a decryption key when the video is played on a digital screen of the second computer device;

generating, by the one or more processors, a second media content frame comprising the first media content frame overlaid by the video; and

transmitting, by the one or more processors, the second media content frame to the second computer device for the second media content frame to be played on the digital screen of the second computer device.

2. The method of claim 1 , wherein the one or more user interface elements comprise at least one of a chat bubble, a soft button, a menu, an icon, or a comment bubble.

3. The method of claim 1 , wherein determining that the one or more user interface elements are present in the first media content frame is performed by executing a machine learning model on the first media content frame, the machine learning model trained based on training data to detect the one or more user interface elements.

4. The method of claim 3 , further comprising:

extracting, by the one or more processors, a feature vector from the first media content frame; and

sending, by the one or more processors, the feature vector as input to the machine learning model for determining that the one or more user interface elements are present in the first media content frame.

5. The method of claim 1 , wherein determining that the one or more user interface elements are present in the first media content frame is performed by optical character recognition or natural language processing.

6. The method of claim 1 , wherein encrypting the video is performed using an advanced encryption standard (AES) algorithm.

7. The method of claim 1 , further comprising:

receiving, by the one or more processors, a request for the decryption key from the second computer device; and

transmitting, by the one or more processors, the decryption key to the second computer device for decrypting the video.

8. A system comprising:

one or more computer processors; and

a non-transitory computer readable storage medium storing computer instructions, which when executed by the one or more computer processors cause the one or more computer processors to:

receive a first media content frame from a first computer device;

determine that one or more user interface elements are present in the first media content frame;

extract the one or more user interface elements from the first media content frame;

convert the one or more user interface elements to video;

encrypt the video to prevent screenshot capture of the one or more user interface elements present in the first media content frame by a second computer device lacking a decryption key when the video is played on a digital screen of the second computer device;

generate a second media content frame comprising the first media content frame overlaid by the video; and

transmit the second media content frame to the second computer device for the second media content frame to be played on the digital screen of the second computer device.

9. The system of claim 8 , wherein the one or more user interface elements comprise at least one of a chat bubble, a soft button, a menu, an icon, or a comment bubble.

10. The system of claim 8 , wherein the instructions to determine that the one or more user interface elements are present in the first media content frame cause the one or more computer processors to execute a machine learning model on the first media content frame, the machine learning model trained based on training data to detect the one or more user interface elements.

11. The system of claim 10 , wherein the instructions cause the one or more computer processors to:

extract a feature vector from the first media content frame; and

send the feature vector as input to the machine learning model for determining that the one or more user interface elements are present in the first media content frame.

12. The system of claim 8 , wherein the instructions cause the one or more computer processors to determine that the one or more user interface elements are present in the first media content frame by optical character recognition or natural language processing.

13. The system of claim 8 , wherein the instructions cause the one or more computer processors to encrypt the video using an advanced encryption standard (AES) algorithm.

14. The system of claim 8 , wherein the instructions cause the one or more computer processors to:

receive a request for the decryption key from the second computer device; and

transmit the decryption key to the second computer device for decrypting the video.

15. A non-transitory computer readable storage medium storing computer instructions, which when executed by one or more computer processors cause the one or more computer processors to:

receive a first media content frame from a first computer device;

determine that one or more user interface elements are present in the first media content frame;

extract the one or more user interface elements from the first media content frame;

convert the one or more user interface elements to video;

encrypt the video to prevent screenshot capture of the one or more user interface elements present in the first media content frame by a second computer device lacking a decryption key when the video is played on a digital screen of the second computer device;

generate a second media content frame comprising the first media content frame overlaid by the video; and

transmit the second media content frame to the second computer device for the second media content frame to be played on the digital screen of the second computer device.

16. The storage medium of claim 15 , wherein the one or more user interface elements comprise at least one of a chat bubble, a soft button, a menu, an icon, or a comment bubble.

17. The storage medium of claim 15 , wherein the instructions to determine that the one or more user interface elements are present in the first media content frame cause the one or more computer processors to execute a machine learning model on the first media content frame, the machine learning model trained based on training data to detect the one or more user interface elements.

18. The storage medium of claim 17 , wherein the instructions cause the one or more computer processors to:

extract a feature vector from the first media content frame; and

send the feature vector as input to the machine learning model for determining that the one or more user interface elements are present in the first media content frame.

19. The storage medium of claim 15 , wherein the instructions cause the one or more computer processors to determine that the one or more user interface elements are present in the first media content frame by optical character recognition or natural language processing.

20. The storage medium of claim 15 , wherein the instructions cause the one or more computer processors to encrypt the video using an advanced encryption standard (AES) algorithm.